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Source channel @githubtrending · Post #15316 · Dec 7

#lua OTClient Redemption is a flexible and complete alternative client for the game Tibia, designed to work with OTServ servers. It uses LUA scripting and CSS-like syntax for easy customization of the game interface, allowing you to create new mods and extend features. Written in modern C++20, it supports advanced graphics, sound, multi-language, and mobile platforms through OpenGL. It offers many features like shaders, animated textures, transparency, and an in-game LUA terminal. This client improves performance with multi-threading and garbage collection, and adapts smoothly to server latency for better gameplay. You benefit by having a customizable, high-performance client that enhances your Tibia experience and supports modding and mobile use. https://github.com/mehah/otclient

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AI & Law

@ai_and_law · Post #286 · 04/16/2024, 07:04 AM

US Federal Agencies Issue Joint Statement on Automated Systems On April 3, 2024, several US federal agencies released a joint statement on the Enforcement of Civil Rights, Fair Competition, Consumer Protection, and Equal Opportunity Laws in Automated Systems. Signatories include leaders from the EEOC, Consumer Financial Protection Bureau, Department of Justice, Federal Trade Commission, Department of Education, Department of Health and Human Services, Department of Homeland Security, Department of Housing and Urban Development, and Department of Labor. The statement underscores the commitment of federal agencies to enforce legal protections applicable to automated systems, defined as software and algorithmic processes, including AI, used to automate workflows and decision-making. Emphasizing the dual objectives of monitoring automated tools' evolution and fostering responsible innovation, agencies reaffirm the relevance of existing laws to automated systems. They stress their role in ensuring compliance with these laws during system development. This follows previous efforts by the EEOC and other agencies to address discrimination and bias in automated systems. The expanded participation in this year's statement reflects the government's heightened focus on regulating automated systems and enforcing relevant laws. The statement emphasizes that AI and automated systems fall under existing laws, dispelling the notion that their "black box" nature exempts them from compliance. It identifies potential sources of unlawful discrimination or bias, including skewed training data, lack of transparency, and inadequate consideration of social context during design and use. Compliance with existing and AI-specific laws is paramount for fostering trust and safe AI innovation, as highlighted in the joint statement. #automatedsystems#AI#AIcompliance